BIG DATA WITH HADOOP & SPARK

Program Objective

Nowadays, the popularity of big data is increasing exponentially so there is a requirement in the big data analyst profile that can extract the relevant data. This course is designed to give a detailed knowledge of Big Data Framework using Hadoop and Spark, including HIVE, PIG, YARN, SCALA, SPARK SQL, SPARK Streaming, PYSPARK and MapReduce. The objective of our program is to develop a better understanding of the basic concepts of statistics in the realm of Big Data. Hence, our program will give you a hands-on real-life industry use cases. As you learn different technologies you will be able to take decisions on how to fit different technologies in order to process the Big Data

Learning Outcomes

After completion of this course, you will be able to design Distributed Systems which can manage Big Data using Hadoop and Spark. In this course, you will learn to use HDFS and MapReduce to store and analysis data at large scale. You will be able to frame Big data problems into Spark problems. You will be able to create scripts to process and analysis data on the Hadoop cluster by using Pig and Hive, using Sqoop and Flume for data ingestion. You will expert consistent data processing of using Spark, consolidating valuable programming in Spark, understanding parallel processing in Spark, completing Spark applications and using Spark RDD streamlining approaches

Features

  • Study Material
  • Placement Assistance.
  • Interview Preparation
  • Experienced and Certified Trainers.
  • Certificate exam from Emerging India
  • Online Assignments

Course Overview

  • Study Material.
  • Placement Assistance
  • Interview Preparation
  • Experienced and Certified Trainers
  • Certificate exam from Emerging India
  • Online Assignments

Course Overview

  • Hadoop Architecture-HDFS, MapReduce
  • Installation of Hadoop Components
  • HIVE
  • PIG
  • HBASE
  • SQOOP
  • FLUME
  • OOZIE
  • KAFKA
  • Introduction to Big Data tool Spark
  • SCALA
  • SPARK SQL
  • SPARK Streaming
  • PYSPARK
  • Mlib
  • GraphX

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